Proceedings of the Annual Meeting of the Cognitive Science Society

In order to determine the manner in which temporal patterns are represented in recurrent neural networks, networks trained on a vari- ety of sequence recognition tasks are exam- ined. Analysis of the state space of unit ac- tivations allows a direct view of the means em- ployed by the network to solve a given prob- lem, and yields insight both into the class of solutions these networks cfm produce and h o w these will generalise to sequences outside the training set. This intuitive approach helps in assessing the potential of recurrent networks for a variety of modelling problems.